metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
- classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tweet-eval-sentiment
results: []
tweet-eval-sentiment
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0651
- Accuracy: 0.4759
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 230 | 1.1097 | 0.3345 |
| No log | 2.0 | 460 | 1.0392 | 0.4609 |
| 1.1042 | 3.0 | 690 | 1.0651 | 0.4759 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2